Assessing the Impact of Lead and Floe Sampling on Arctic Sea Ice Thickness Estimates from Envisat and CryoSat‐2

Tilling, Rachel; Ridout, A.; Shepherd, A.

doi:10.1029/2019jc015232

Cited by 29 publications

(46 citation statements)

References 24 publications

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“…Since the pulse-limited radar altimeter footprint is rather rough, basically larger than 2 km, the reflection from the leads can affect the detection of shorter and thinner ice of Envisat (Tilling et al, 2019). Therefore, Envisat tends to detect wider and thicker sea ice leading to higher freeboard in the first-year ice (Schwegmann et al, 2016;Tilling et al, 2019). The preference for wider sea ice floes may cause overestimation of ice thickness compared with the laser altimeter loaded on ICESat.…”

Section: Deviations Due To Different Sensorsmentioning

confidence: 99%

A comparison between Envisat and ICESat sea ice thickness in the Antarctic

Wang

Min

Ricker

et al. 2020

Preprint

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Abstract. The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness. While in situ observations are too sparse in the Antarctic to determine long-term trends of the Antarctic sea ice thickness on a global scale, satellite radar altimetry data can be applied with a promising prospect. A newly released Envisat-derived product from the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI), including sea ice freeboard and sea ice thickness, covers the entire Antarctic year-round from 2002 to 2012. In this study, the SICCI Envisat sea ice thickness in the Antarctic is firstly compared with a conceptually new proposed ICESat ice thickness that has been derived from an algorithm employing modified ice density. Both data sets have been validated with the Weddell Sea upward looking sonar measurements (ULS), indicating that ICESat agrees better with field observations. The inter-comparisons are conducted for three seasons except winter based on the ICESat operating periods. According to the results, the deviations between Envisat and ICESat sea ice thickness are different considering different seasons, years and regions. More specifically, the smallest average deviation between Envisat and ICESat sea ice thickness exists in spring by −0.03 m while larger deviations exist in summer and autumn by 0.86 m and 0.62 m, respectively. Although the smallest absolute deviation occurs in spring 2005 by 0.02 m, the largest correlation coefficient appears in autumn 2004 by 0.77. The largest positive deviation occurs in the western Weddell Sea by 1.03 m in summer while the largest negative deviation occurs in the Eastern Antarctic by −0.25 m in spring. Potential reasons for those deviations mainly deduce from the limitations of Envisat radar altimeter affected by the weather conditions and the surface roughness as well as the different retrieval algorithms. The better performance in spring of Envisat has a potential relation with relative humidity.

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Section: Deviations Due To Different Sensorsmentioning

confidence: 99%

A comparison between Envisat and ICESat sea ice thickness in the Antarctic

Wang

Min

Ricker

et al. 2020

Preprint

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“…Details on the processing of the CryoSat-2 waveform, used to produce a dataset of floe chords spanning the period 2010-2018, are outlined in Sect. 3 and Tilling et al (2019b).…”

Section: Floe Chords and The Floe Size Distributionmentioning

confidence: 99%

Estimating the sea ice floe size distribution using satellite altimetry: theory, climatology, and model comparison

et al. 2019

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Abstract. In sea-ice-covered areas, the sea ice floe size distribution (FSD) plays an important role in many processes affecting the coupled sea–ice–ocean–atmosphere system. Observations of the FSD are sparse – traditionally taken via a painstaking analysis of ice surface photography – and the seasonal and inter-annual evolution of floe size regionally and globally is largely unknown. Frequently, measured FSDs are assessed using a single number, the scaling exponent of the closest power-law fit to the observed floe size data, although in the absence of adequate datasets there have been limited tests of this “power-law hypothesis”. Here we derive and explain a mathematical technique for deriving statistics of the sea ice FSD from polar-orbiting altimeters, satellites with sub-daily return times to polar regions with high along-track resolutions. Applied to the CryoSat-2 radar altimetric record, covering the period from 2010 to 2018, and incorporating 11 million individual floe samples, we produce the first pan-Arctic climatology and seasonal cycle of sea ice floe size statistics. We then perform the first pan-Arctic test of the power-law hypothesis, finding limited support in the range of floe sizes typically analyzed in photographic observational studies. We compare the seasonal variability in observed floe size to fully coupled climate model simulations including a prognostic floe size and thickness distribution and coupled wave model, finding good agreement in regions where modeled ocean surface waves cause sea ice fracture.

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“…For an individual pass over sea ice by a polar-orbiting satellite altimeter, return waveforms along the satellite orbit track are assigned a surface type depending on the waveform shape and coincident sea ice concentration (Tilling et al, 2018b). A "floe chord" of length D is a continuous series of points identified as sea ice, covering a geographic distance D (Tilling et al, 2018a(Tilling et al, , 2019. Define a floes size, r, as its "effective radius" -the square root of the floe's area divided by π (Rothrock and Thorndike, 1984a;Horvat and Tziperman, 2015).…”

Section: Floe Chords and The Floe Size Distributionmentioning

confidence: 99%

“…Details on the processing of the CryoSat-2 waveform, used to produce a dataset of floe chords spanning the period 2010-2018, is outlined in Sec. 3 and Tilling et al (2019).…”

Section: Floe Chords and The Floe Size Distributionmentioning

confidence: 99%

“…However, surface discrimination via altimetry is highly accurate in months without melt ponds (Peacock and Laxon, 2004;Guerreiro et al, 2017;Quartly et al, 2019), giving confidence that two consecutive floe echos, the minimum length scale represented here, represent a coherent length of ice. Indeed, this raw floe chord data has been used successfully to reduce biases in altimeter-observed satellite sea ice thickness estimates from satellite altimeters with different footprint sizes (Tilling et al, 2018a(Tilling et al, , 2019). Here we analyze the sea ice floe size distribution using that floe chord product.…”

Section: Evaluating the Floe Size Power-law Hypothesis With Floe Chormentioning

confidence: 99%

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Estimating The Sea Ice Floe Size Distribution Using Satellite Altimetry: Theory, Climatology, and Model Comparison

Horvat¹,

Roach²,

Tilling³

et al. 2019

Preprint

Self Cite

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Abstract. In sea-ice-covered areas, the sea ice floe size distribution (FSD) plays an important role in many processes affecting the coupled sea-ice-ocean-atmosphere system. Observations of the FSD are spare – traditionally taken via a pain-staking analysis of ice surface photography – and the seasonal and inter-annual evolution of floe size regionally and globally is largely unknown. Frequently, measured FSDs are assessed using a single number, the scaling exponent of the closest power law fit to the observed floe size data, although in the absence of adequate datasets there have been limited tests of this power-law hypothesis. Here we derive and explain a mathematical technique for deriving statistics of the sea ice FSD from polar-orbiting altimeters, satellites with sub-daily return times to polar regions with high along-track resolutions. Applied to the CryoSat-2 radio altimetric record, covering the period from 2010–2018, and incorporating 11 million individual floe samples, we produce the first climatology and seasonal cycle of sea ice floe size statistics. We then perform the first pan-Arctic test of the power law hypothesis, finding limited support in the range of floe sizes typically analyzed in photographic observational studies. We compare the seasonal variability in observed floe size to fully coupled climate model simulations including a prognostic floe size and thickness distribution and coupled wave model, finding good agreement in regions where modeled ocean surface waves cause sea ice fracture.

show abstract

Assessing the Impact of Lead and Floe Sampling on Arctic Sea Ice Thickness Estimates from Envisat and CryoSat‐2

Cited by 29 publications

References 24 publications

A comparison between Envisat and ICESat sea ice thickness in the Antarctic

A comparison between Envisat and ICESat sea ice thickness in the Antarctic

Estimating the sea ice floe size distribution using satellite altimetry: theory, climatology, and model comparison

Estimating The Sea Ice Floe Size Distribution Using Satellite Altimetry: Theory, Climatology, and Model Comparison

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